Application of smart phone agro-advisory services of m4agriNEI in climate smart natural resource management in agriculture by tribal farmers of Meghalaya: an empirical study with structural equation modeling

  • RJ Singh
  • Ram Singh
  • NJ Singh
  • TS Anurag
  • Bai Koyu

Abstract

Smart phone applications are increasingly being used by farmers of North East India to help them make informed decision on Climate-Smart Natural Resource Management (CSNRM). The research project m4agriNEI is an innovative mix of Smart Phone and web applications along with Toll Free IVRS based farmer specific agro-advisory system being implemented at College of P.G. Studies in Agricultural Sciences of CAU, Imphal at Umiam, Meghalaya in collaboration with Digital India Corporation, New Delhi. The present study aims to investigate and confirm a successful model application of smart phone Agro-Advisory Services (AAS) by the registered farmers of m4agriNEI by incorporating five constructs through Structural Equation Modelling on CSNRM in Agriculture. Survey research design was followed in the study by incorporating exploratory and confirmatory factor analysis. A total of 363 registered farmers were treated as respondents in the study. The study unveiled that ‘Smart Phone Agro-Advisory Services Acceptance Model’ of m4agriNEI is a successful model on empowering the tribal farmer of Meghalaya in climate smart natural resource management in agriculture by providing right information in right time through a smart phone based agro-advisory system.

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References

Ajzen I. 1991. The theory of planned behavior. Organizational Behaviour and Human Decision Processes, 50: 179-211.
Bryman A & Cramer D. 2005. Quantitative data analysis with SPSS 12 and 13. London: Routledge.
Chau P. 1996. An empirical investigation on factors affecting the acceptance of CASE by systems developers. Information & Management, 30: 269-280.
Chen G & Kotz D. 2000. A survey of context-aware smart phone computing research (Dartmouth Computer Science Technical Report).
Cho D, Kwon H & Lee H. 2007. Analysis of trust in internet and Smart Phone commerce adoption. In The 40th Hawaii international conference on system science.
Gao S, Krogstie J & Gransæther P. 2008. Smart Phone services acceptance model. In International conference on convergence and hybrid information technology (pp. 446e453) (Daejeon, Korea).
Gao S, Krogstie J & Siau K. 2011. Developing an instrument to measure the adoption of Smart Phone services. Smart Phone Information Systems, 7: 45-67.
Government of Meghalaya (GoM). 2016. Meghalaya Agriculture Profile, Department of Agriculture, Government of Meghalaya.
Hair J, Black W, Babin B & Anderson R. 2010. Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Pearson Education.
Hu L & Bentler P. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modelling: A Multidisciplinary Journal, 6(1): 1-55.
Mallat N, Rossi M, Tuunainen V & Oorni A. 2009. The impact of use context on Smart Phone services acceptance: The case of Smart Phone ticketing. Information & Management, 46(3): 190-195.
Marchewka J & Liu C. 2007. An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7(2): 93-104.
Mou J & Cohen J.(2014. A longitudinal study of trust and perceived usefulness in consumer acceptance of an e-service: The case of online health services. Pacific Asia Conference on Information Systems (PACIS).
Nunnally J. 1978. Psychometric Theory. McGraw-Hill: New York.
Sarker S & Wells D. 2003. Understanding Smart Phone handheld device use and adoption. Communications of the ACM, 46(12): 35-40.
Schierz P, Schilke O & Wirtz B. 2010. Understanding consumer acceptance of Smart Phone payment services: An empirical analysis. Electronic Commerce.
Tabachnick B & Linda S. 2007. Using multivariate statistics. Boston: Pearson/Allyn & Bacon.
Published
2020-07-30
How to Cite
SINGH, RJ et al. Application of smart phone agro-advisory services of m4agriNEI in climate smart natural resource management in agriculture by tribal farmers of Meghalaya: an empirical study with structural equation modeling. Journal of Agriculture and Ecology, [S.l.], v. 9, p. 67-77, july 2020. ISSN 2456-9410. Available at: <http://journals.saaer.org.in/index.php/jae/article/view/293>. Date accessed: 25 nov. 2020.
Keywords
AAS, ICT, m4agriNEI, Climate-Smart Natural Resource Management, Structural Equation Modeling